This work presents AICOS (Artificial Intelligence Control & Oversight System), a governance-first mathematical framework designed to ensure safe and controlled decision-making in high-impact environments under uncertainty and irreversibility. Traditional artificial intelligence and decision systems primarily focus on prediction accuracy and optimization. However, real-world decisions—particularly in finance, energy, and critical infrastructure—are subject to uncertainty, systemic risk, and irreversible consequences. These conditions invalidate classical assumptions of expected utility theory and require a fundamentally different approach. AICOS introduces a unified decision architecture integrating: Risk modeling (extended beyond classical probability-based frameworks) Uncertainty quantification and control (including uncertainty lock mechanisms) Constraint enforcement (regulatory, financial, and physical limits) Deterministic replay and auditability (hash-based decision traceability) Governance-first decision control with human-final authority The framework is mathematically formalized through a unified decision equation and a set of necessity and sufficiency theorems demonstrating that safe decision systems must simultaneously satisfy risk control, uncertainty control, constraint enforcement, and auditability conditions. In addition, the work extends classical models in multiple domains: Credit risk modeling (PD, LGD, EAD) enhanced with macroeconomic irreversibility and uncertainty factors Inflation-adjusted real return modeling, distinguishing between nominal and effective economic outcomes Energy CAPEX decision frameworks incorporating irreversibility and geopolitical risk Monte Carlo simulation-based scenario engines (50,000+ scenarios) for tail-risk evaluation System-level risk propagation modeling across interconnected financial and geopolitical systems The results show that optimization-only AI systems are mathematically insufficient for high-impact decision environments. Instead, a governance layer—such as AICOS—is required to ensure stability, accountability, and regulatory compliance. AICOS is therefore not presented as a conventional AI model, but as a Decision Governance Infrastructure—a control and oversight layer that transforms AI-driven outputs into safe, auditable, and regulator-grade decisions. This work positions AICOS as a foundational framework for next-generation decision systems across finance, energy, and critical infrastructure, with potential implications for global AI governance standards.
YASIN KALAFATOGLU (Sun,) studied this question.